Evidence map›Paper›PMID 29204318›Full record

ArticlePeerJ2017

Kullback Leibler divergence in complete bacterial and phage genomes.

Sajia Akhter, Ramy K Aziz, Mona T Kashef, Eslam S Ibrahim, Barbara Bailey, Robert A Edwards

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact, top 86% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Investigating Metrics of Discrete-Individual Repeatability of the Stress Response.Integrative organismal biology (Oxford, England) · 2025
    Article
  3. Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Sajia AkhterComputational Science Research Center, San Diego State University, San Diego, CA, USA.
Ramy K AzizDepartment of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
Mona T KashefDepartment of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
Eslam S IbrahimDepartment of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
Barbara BaileyDepartment of Mathematics & Statistics, San Diego State University, San Diego, CA, USA.
Robert A EdwardsComputational Science Research Center, San Diego State University, San Diego, CA, USA.
Cairo University · EGSan Diego State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback-Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses.

Indexed as

GenometricsGenomicsInformation theoryMetagenomics

Identifiers

PMID29204318
PMCPMC5712468
OpenAlexW2774492855

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.